HerdPlus: SeH for optimised sampling strategy

Input Values

Test Sensitivity:
Test Specificity:
Maximum herd sensitivity:
Minimum herd specificity:
Animal-level design prevalence:
Use specified proportion
Calculate as 1/N for each herd size
Animal-level design prevalence value:
Herd-level design prevalence:
Target number of herds tested:
Target system sensitivity for optimised strategy:
Precision (significant digits):
Number of meta simulations:
Number of iterations for each meta-simulation:


This module takes several minutes to run, depending on numbers of iterations and simulations requested. Enter your email address and an email will be sent to you with a link to the results.

Calculate optimised sample size and cut-point and resulting herd sensitivity (SeH) and herd specificity (SpH) for a specified list of herd sizes, test sensitivity, test specificity and design prevalence. Animal-level design prevalence can be specified as a fixed proportion, or as the equivalent of one animal per herd. Sample size and cut-point are constrained to provide SeH less than or equal to a specified maximum value and SpH greater than a specified minimum value. Sample sizes are also constrained to be no more than the specified value corresponding to each herd size.

A meta-simulation is also run, using the optimised SeH and SpH for each herd size, to calculate the number of herds required to be tested to achieve a specfied target system sensitivity (SSe). SSe achieved and the number of animals to be tested from a specified number of herds selected at random from the population are also calculated.

Inputs include:

  • Test sensitivity and specificity;
  • Maximum desired SeH and minimum SpH;
  • Mode of setting design prevalence, either as a specified value or as a proportion of herd size;
  • Animal-level design prevalence (only required if option for specified design prevalence is selected);
  • Herd-level design prevalence;
  • Target number of herds to be tested from population;
  • Target system sensitivity (SSe) for population testing scheme;
  • Number of iterations per simulation and number of simulations for meta-simulation of population testing; and
  • The desired precision of results (number of digits to be displayed after the decimal point).
  • Pasted data comprising columns for herd size and corresponding maximum sample size and counts or relative frequency of each herd size in the population. Include a row of column headings in the data.

Note: Large numbers of meta-simulations generally provide only minimal additional benefit and may result in a system crash if used in combination with large numbers of iterations. A maximum of 100 meta-simulations is usually ample.

Results are calculated using the HerdPlus method (Greiner 2006?) and include:

Results are calculated using the HerdPlus method (Greiner 2006?) and include:

  • Table of optimised sample sizes and cut-points and corresponding SeH and SpH values for each specified herd size;
  • Plot of SeH and SpH values for optimised sample size and cut-point against herd size.
  • Summary table of meta-simulation results including median and 5th/95th percentiles of the numbers of herds required to achieve the target SSe and the achieved SSe and number of animals tested under the optimised scheme for the specified number of herds tested; and
  • Detailed results of meta-simulations.


Developed by Matthias Greiner and Evan Sergeant

Paste the data to be analysed in the space below and click on submit:
1st column is herd size, 2nd column is maximum sample size and 3rd column is count or relative frequency for each herd size. Include a header row of column names.

Download example herd data


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